Monocular Image Depth Estimation via Vanishing Point Geometry
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Solution Overview
Problem
Existing methods for determining real-world distances or depths from monocular images are inaccurate and require multiple images or stereo setups, making them inefficient for location-based services like autonomous driving, which rely on precise and single-image-based data.
Innovation Solution
A method that determines the vanishing point in a monocular image, generates rays from the optical center to infinity, and computes horizontal distances or depths using image coordinate data and angles, allowing for accurate real-world distance estimation from a single image.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple images or stereo setups are used to determine real-world distances, then measurement precision is improved, but device complexity and productivity are worsened
Solution Approach 1:
The patent extracts and utilizes the vanishing point geometric property from the monocular image to derive depth information. By identifying the vanishing point where parallel lines converge in the image plane and using its geometric relationship with the optical center, the system extracts sufficient depth information without requiring multiple images or stereo setups, thus resolving the contradiction between measurement precision and device complexity
Solution Approach 2:
The vanishing point acts as an intermediary geometric element that mediates between the 2D image plane and the 3D real-world space. By introducing the vanishing point ray as an intermediary structure connecting the optical center to the vanishing point on the image plane, the system enables accurate depth measurement through geometric relationships rather than requiring complex multi-image or stereo systems
2Measurement precision
If multiple images or stereo setups are used to determine real-world distances, then measurement precision is improved, but productivity is worsened
Solution Approach 1:
The patent extracts depth information directly from a single monocular image by utilizing the vanishing point geometric property. This extraction approach eliminates the need to process multiple images or stereo image pairs, significantly improving processing efficiency and productivity while maintaining accurate distance estimation through the geometric relationship between the optical center, vanishing point, and image plane
Solution Approach 2:
The patent segments the depth estimation problem into independent geometric components: identifying the vanishing point, determining the optical center, calculating the vanishing point ray, and computing the feature ray. This segmentation allows for efficient parallel processing and reduces the overall computational complexity compared to processing multiple images sequentially
3Device complexity
If monocular image processing is used, then device complexity is reduced, but measurement precision is worsened
Solution Approach 1:
The vanishing point ray serves as a geometric intermediary that enables accurate depth measurement in monocular images. By constructing the vanishing point ray from the optical center through the vanishing point on the image plane to infinity, and combining it with the feature ray from the optical center through the feature pixel location, the system achieves precise distance estimation using only single-image geometric relationships
Solution Approach 2:
The patent transforms the 2D monocular image information into 3D spatial understanding by introducing the vanishing point ray dimension. The vanishing point ray extends from the optical center through the vanishing point to infinity, creating a third dimension that enables accurate depth calculation. This dimensional transformation allows the system to recover real-world distances from 2D image data without requiring multiple images
Data Source
AI summary
An approach is provided for estimating a real-world depth information from a monocular image. The approach, for example, involves determining a vanishing point of the monocular image captured by a camera. The approach also involves generating a vanishing point ray from an optical center of the camera through the vanishing point on an image plane of the monocular image to infinity. The approach further involves generating a center line ray from the optical center through a geometric center of the image plane to a feature line that is parallel to the vanishing point ray at a lateral distance. The approach further involves generating a feature ray from the optical center through a location of the feature on the image plane to the feature line. The approach further involves computing the real-world distances of the feature based on image coordinates of the rays, lines, angles derived therefrom, and a known pixel-wise distance of the monocular image.